THE EFFECT OF IMPLEMENTING GCG (GOOD CORPORATE GOVERNANCE), WITH GGE (GREEN-GROWTH ECONOMY) AS A MODERATING VARIABLE OF FINANCIAL PERFORMANCE ON INCREASING ECONOMIC INCOME THROUGH
GDP/GNP POST-TOWARDS THE NEW NORMAL
(Empirical Study Of Property & Real Estate Sub-Sector Companies Whose Shares Are Listed On The Indonesian Stock Exchange Development Board 2020-2023) Margaretha Prihatiningsih, Yusup Hari Subagyo, Elisabeth Francisca Sibarani,
Intan Paska, Felix Ikko
Universitas Pignatelli Triputra Surakarta Email : [email protected]
Abstract
Research with the title: "The Effect of Implementing GCG (Good Corporate Governance), With GGE (Green Grouwth Economy) as a Moderating Variable of Financial Performance on the GNP/GDP of Development Board Companies whose Shares are Listed on the BEI (Indonesian Stock Exchange) for the 2020-2022 Observation Period aims to Knowing How the Implementation of GCG Influences Financial Performance CAR Liquidity, DAR & DER Solvency, NPM Profitability & ROA Profitability, ROE & ROI and Tobinsq can increase GDP/GNP through the moderation variable GGE can spur an increase in GDP/GNP for Development Board Companies whose shares are listed on BEI. Implementation of GCG (Good Corporate Governance), with GGE (Green Grouwth Economy) as a moderating variable will spur GDP/GNP. The methodology used is the Quantitative Method with Multiple Correlation Regression Test, Anova TEST F & T-test and R Quadrate to calculate and test data on variables X & Y from the population taken in this research, namely all companies whose shares are listed on the BEI Development Board (Period 2020 to 2023 there are 372 companies). Meanwhile, the sample of 80 companies met the sampling criteria and covered all the variables studied and had Financial Reports for 3 consecutive years, with a complete Report Development Board Annual Report for 17 companies. Based on MRA analysis, the following results were obtained: (1) The influence of ROI, & CAR on GNP (Y1) through GGE (Z1) with a significant value of 0.036; 0.024 is below 0.05. So ROI & CAR through GGE (Z1) are able to influence GNP (Y1), which means the hypothesis is accepted. (2) The influence of DER, &
Tobinsq on GNP (Y1) through GGE (Z1) shows a significant value of 0.024, 0.027 below 0.05. So DER &
Tobin's Q through GGE (Z1) is able to influence GNP (Y1), which means the hypothesis is accepted.
Results of Analysis 2: (1) The influence of ROA, CAR, & Tobins Q on GNP (Y1) through GCG (Z1) The t calculated regression value of ROA, CAR, & Tobinsq with a significant value of 0.001; 0.036; 0.000 under 0.05. So ROA, CAR & Tobinsq through GCG (Z1) are able to influence GNP (Y1) which means it is acceptable. Based on the results of Analysis 3 as follows: (1) Effect of Tobin's Q, ROA; ROI, DER to GDP (Y2) via GGE (Z1) as a mediating variable - with a significant value of 0.827; above 0.05; while 0.001; 0.026; 0.011; & 0.000 below 0.05. So Tobin's Q; ROA; ROI; DER via GGE (Z1) is unable to influence GDP (Y2) which means it is rejected, while var ROA, ROI & DER is accepted. Based on the results of the MRA 5 analysis as follows: (1) ROA, ROI through GGE (Z2) is able to influence GDP (Y2) which means it is acceptable. (2) Based on Analysis Results (6) as follows: (1) Influence of ROA; ROI;
DER; TobinsQ; ROE, on GDP (Y2) through GGE (Z2) as a mediating variable can indirectly influence GDP (Y2), which means it is acceptable.
Keywords: GCG, GGE, Moderating Variables, MRA, Financial Performance Liquidity, Solvency, Profitability, Profitability, GDP/GNP.
1. Introduction
The development of the capital market in the business world, spurring the acceleration of infrastructure development is not without reason, because infrastructure has an important influence on improving the quality of life and human welfare, including increasing the value of consumption, increasing labor productivity, and access to employment opportunities, as well as increasing real prosperity and the realization of macroeconomic stabilization, namely: fiscal sustainability, development of the credit market and its impact on the labor market. The large number of investors who are starting to invest their shares in property, real estate and building construction companies will enable development companies to obtain equity capital to carry out large projects to increase company income. Investors who will invest by buying shares in the capital market will first analyze the condition of the company in order to get returns which are always expected to increase.
In this research, the aim is that in the future investors will be able to read, understand and understand the meaning of financial reports, so they need to be analyzed first with various analytical tools that can be used. (Kasmir, 2019:4) states that analysis of financial performance shows that the results of liquidity, solvency, profitability and profitability of development board companies whose shares are listed on the Indonesia Stock Exchange (BEI) are getting better.
Business owners can find out the company's financial condition and assess current progress, whether it has achieved the targets that have been set or not. Meanwhile, for management, financial reports are a reflection of their financial condition and performance during the reporting period.
The results of the financial report analysis will provide an overview and can be used to determine the direction and goals of the company. This means that financial reports can be a reference in making decisions and matters that are considered important for management.
Financial analysis tools commonly used are financial ratios such as: liquidity ratio (Ningsih, 2020), solvency ratio (Salim, 2021), profitability ratio (Nurfinda, 2019), activity ratio (Novitasari, 2020), gross profit analysis and other ratios . (Kasmir, 2019: 5) states that it is also very important for investors to invest their capital in a company to pay attention to how GCG (Good Corporate Governance) is implemented within internal development board companies, where good governance in all areas internally will show that the company It still exists and future prospects are getting better and more advanced, as well as for the long-term sustainability of its business.
The reason why researchers include GCG as a Moderation variable is a variable that can strengthen or weaken the influence of variable accountability, responsibility, independence and fairness) are very important triggers to always monitor for improvement so that it shows that the Manager's performance has increased and progressed. If so, the manager's performance will support financial performance which can increase GDP & GNP. Abdullah and Ismail (2016) researched the connection between Good Governance (GCG) and financial performance in the GCG area and found that GCG as proxied by Institutional Ownership had a very large influence on financial performance.
The results of previous research show that there are still many inconsistencies found which require other variables to moderate financial performance other than GCG, so in this research the researcher tries to carry out replication research on this GCG topic to display the GGE variable as a supporting moderating variable so as to stimulate the relationship between these variables. Likewise, Investors and Managers are very concerned about the environment,
which in this case is shown by GGE (Green Grouwth Economy) Performance, the measurement of which can be seen from the company's activities towards: (1) Sustainable economic growth;
(2) Inclusive and equitable growth; (3) Socio-economic and environmental growth; (4) A healthy and productive ecosystem provides environmental improvement services; (5) Reduction of gas and greenhouse emissions. If the company's activities have been carried out well, with a Full Employment capacity of 100%, it will ensure that the company's survival in the long term can be achieved. This will show that GGE Performance can support Financial Performance which will ultimately have a positive impact on increasing a country's GDP / GNP. So it can be concluded that this research model that uses the GGE Moderation Variable as a support for the influence of financial performance on increasing a country's GDP/GNP is very appropriate in this era towards the New Normal.
From the description of the research background, the researcher took the research title:
"The Effect of Implementing GCG (Good Corporate Governance), With GGE (Green Growth Economy) as a Moderating Variable of Financial Performance on Increasing Economic Income through GDP/GNP Post-Towards the New Normal (Empirical Study in Property & Real Estate Sub-Sector Companies whose Shares are Listed on the Development Board (Indonesian Stock Exchange) in 2020-2022.
Problem Formulation.
From the description of the background of the problem, the problem can be formulated as follows: (1) Does the implementation of GCG (Good Corporate Governance) affect financial performance variations? ROA (X1), ROE (X2), ROI (X3), CAR (X4), DER (X5), DAR (X6), NPM (X7) & Tobins-Q (X8) Moderated by GGE (Green Growth Economy) or Z2 against GNP (Y1) & GDP (Y2). has a significant positive effect on increasing GDP/GNP (Gross Domestic Product / Gross National Product) of companies whose shares are listed on the Indonesian Stock Exchange (BEI) Development Board? (2) What is GGE (Good Corporate Governance) as a moderating variable for financial performance with the variables ROA (X1), ROE (X2), ROI (X3), CAR (X4), DER (X5), DAR (X6), NPM (X7 ) & Tobins-Q (X8) have a significant positive effect on increasing GDP/GNP (Gross Domestic Product / Gross National Product) of companies whose shares are listed on the Indonesian Stock Exchange (BEI) Development Board. (3) What is GCG (Good Corporate Governance) with GGE (Green Growth Economy) as a moderating variable can strengthen or weaken the significant positive influence of financial performance on increasing GDP/GNP (Gross Domestic Product / Gross National Product) of companies whose shares are listed on the BEI Development Board (Indonesian Stock Exchange) (4). How can GCG (Good Corporate Governance) with GGE (Green Growth Economy) as a moderating variable strengthen or weaken its influence on increasing GDP/GNP (Gross Domestic Product/Gross National Product) of Development Board Companies on the Indonesia Stock Exchange (BEI)?
In this research, the researcher focuses more on how to implement GCG (Good Corporate Governance) in facing challenges and company growth in the future of this New Normal Era?
How to utilize GCG (Good Corporate Governance) principles. Business ethics guidelines and codes of conduct are applied so that they are useful in achieving greater goals in the future for the surrounding environment related to the implementation of GCG (Good Corporate Governance) and GGE (Green Growth Economy) as moderating variables in achieving an increase in GDP/GNP (Gross Domestic Product). / Gross National Product) especially for
companies whose shares are listed on the development board on the BEI (Indonesian Stock Exchange).
Research Framework
The framework for thinking in this research can be described as follows:
Independent Variable Dependent variable Variabel Moderasi
Information :
Independent Variable X1 : CAR X4 : ROE, ROI X2 : ROA, NPM
X3 : DAR, DER
Moderating Variable: Dependent Variable Mo-1 : GCG Y1 = GDP
Mo-2 : GGE Y2 = GNP
Description and Measurement of Variables CAR is measured by the formula:
CAR = Current Assets CASH / Total Current Liabilities x 100%
ROA = EAT net profit / Total Assets x 100%
ROE = EAT net profit / Total Equity x 100%
ROI = EAT net profit / Total Assets x 100 %
NPM = Net Profit / Total Net Income (Net Income) x 100%
DAR = Total Debt / Total Assets x 100%
DER = Total Debt / Total Equity.
Financial performance:
Liquidity : CAR Solvency: DAR,
DER Profitability: ROA,
NPM Profitability: ROE,
ROI
GCG (Mo-1)
GGE (Mo-2)
GDP (Y1)
GNP (Y2)
GCG (Good Corporate Governance) can be measured by the checklist results of Transparency, Accountability, Responsibility, Fairness & Equality, Independence. GCG can also be measured from the results of the checklist. GCG variables are seen from the relationship between Shareholders, Management Board, Company Managers/Creditors & Government. (See attachment).
Data Tabulation Appendix 8. Results of the 9 GGE item checklist, namely: (1) Poverty reduction program, (2) Social inclusion, (3) Environmental sustainability, (4) HR efficiency, (5) Investment, (6) Financial performance, (7) ) Fast growth, (8) Decent living standards, (9) Sustainability of Infrastructure. GGE (Green Growth Economy) as a Moderating Variable can be measured from (Mo-1) GNP, (M0-2)NNP & (Mo-3)NP. Growth is measured using the formula.
Method for calculating the level of economic growth. Simple method using the formula: r(t-1,t)
= GDPt – GDP t-1 divided by GDP t-1 multiplied by 100%. GDP/GNP, namely Data Tabulation Appendix 5 Dependent Variables GNP and GDP can be calculated using the following formulas:
GNP = GDP + (PFLN-PFDN). While GDP = C + I + G + (X-M) Hypothesis Formulation
The hypothesis contains a short statement that is concluded from the theoretical basis and/or literature review and is a temporary answer (allegation) to the problem being studied. A hypothesis is always formulated in the form of a statement that connects two or more variables.
The hypotheses in this research include major hypotheses which are then explained in detail into hypotheses per variable. H1: The application of GCG (Good Corporate Governance) as a moderating variable can strengthen or weaken the significant positive influence of financial performance on increasing GDP/GNP (Gross Domestic Product / Gross National Product) of companies whose shares are listed on the BEI Development Board (Indonesian Stock Exchange). H-2: The application of GGE (Good Corporate Governance) as a moderating variable can strengthen or weaken the significant positive influence of Financial Performance on increasing GDP/GNP (Gross Domestic Product / Gross National Product) of Companies whose Shares are Listed on the BEI Development Board (Indonesian Stock Exchange) . H-3:
Implementation of GCG (Good Corporate Governance), GGE (Green Growth Economy) as moderating variables can strengthen the significant positive influence of Financial Performance on increasing GDP/GNP (Gross Domestic Product / Gross National Product) of Companies whose Shares are Listed on the BEI Development Board (Indonesia stock exchange). H-3:
Implementation of GCG (Good Corporate Governance) with GGE (Green Growth Economy) as a moderating variable can strengthen or weaken its influence on increasing GDP/GNP (Gross Domestic Product / Gross National Product) Development Board Company on BEI.
2. Research Methodology
The data analysis method was carried out using MRA (Moderating Regression Analysis) to see the effect of implementing GCG, with GGE as a moderating variable on the increase in GDP/GNP after the New Normal. In this research, the moderating variables GCG & GGE are used. GCG is corporate governance which is the company's principles for maximizing company value, improving performance and maintaining company sustainability in the long term. Based on statements that support the results of Herawaty's (2008) research, it proxies GCG in 4 variables, namely Institutional Ownership, Managerial Ownership, Independent Commissioners and Audit Committee. Meanwhile, the indicators used to assess (the GCG assessment include: 1)
Commitment to implementing good corporate governance as a whole. sustainable, 2) Shareholders and GMS/ Capital Owners, 3) Board of Commissioners,/ Supervisory Board, 4) Directors. 5) Information Disclosure & Transparency. Based on the description above, the implementation of GCG can be measured by CGPI. Financial performance is measured by Return On assets (ROA), Return On Equity (ROE) and Tobins.Q. There are 3 approaches to implementing GCG using the following stages (Chinn, 2000; Shaw, 2003). This stage consists of: 3 main steps, namely 1) Awareness building, 2) GCG Assessment, and 3) GCG manual building. Meanwhile, the 5 GCG Principles at WIKA Beton include 1) Transparency, 2) Accountability, 3) Responsibility, 4) Independence and 5) Fairness. The requirements for implementing GCG are basic principles, including: Participatory, rule of law (law enforcement), transparency, responsiveness, consensus, equal rights, activity and efficiency and accountability.
Constraints The causes of GCG not running well in Indonesia are internal constraints, external constraints, constraints originating from the ownership structure....Meanwhile GGE uses a 9 item checklist, namely: (1) Poverty reduction program, (2) Social inclusion, (3) Environmental sustainability, (4) HR efficiency, (5) Investment, (6) Financial performance, (7) Fast growth, (8) Decent living standards, (9) Infrastructure sustainability. To test the hypothesis from the variables above, the following regression equation is used: Y = Alpha + Beta1X1 + Beta2X2 + Beta3X3 + Beta4X4 + Beta5X5 +e. Information: Y = GDP/GNP, Alpha = Constant. Beta1 = First regression coefficient, namely the magnitude of the change in Y if X1 changes by one unit.
X1= Liquidity. Beta2 = The second regression coefficient is the magnitude of the change in Y if X2 changes by one unit. X2 = Solvency of one unit. X3= Profitability. Beta4 = The fourth regression coefficient, namely the magnitude of the change in Y if X4 changes by one unit. X4 = profitability. Beta5 = The fifth regression coefficient, namely the magnitude of the change in Y if X5 changes by one unit. X5 = Activity Ratio. e : Error term (error rate in research). GGE (Green Growth Economy) is a green economic concept which is a global strategy related to the social, economic and environmental crisis. The creation of a paradigm for the green economy from society methodologically, conceptualization, implementation and criticism leads to the challenge of a global strategy that has sustainable goals, poverty alleviation, inclusion of vulnerable social sectors. The influence of the green economy on the sustainability of life is still in a mental context. The aim of the research is to determine the influence green economy towards economic recovery and multilateral issues. This research is descriptive research that uses types or literature studies. The results of previous research reveal that the implementation of a green economy is able to encourage national economic recovery as well as problems in the multilateral sector. In order for a green economy to be realized for the country, policy makers must be supported by various parties so that a sustainable green economy is formed. The Green Economy also contributes to maintaining a healthy environment and shaping the ecosystem appropriately for current and future generations. Green Economy Indicators. Economic growth is a macro indicator that has a big influence on improving people's welfare. According to Plames (2012), economic growth is very important for society because it is reflected in an increase in goods and services that can improve people's standard of living (Palmer, 2012) which is reflected in an increase in GDP/GNP. Arka (2021) states that economic growth is a phenomenon that aims to increase national income, which will minimize the harmful impacts of economic activities on the environment (WorldBank, 2012). Many studies have tried and formulated ways to measure green, inclusive economic growth and determine its constituent indicators. Green Growth Knowledge Platform (2016) uses natural assets, resource efficiency & decoupling, risk
and resilience, economic opportunities and efforts and inclusiveness as forming indicatorsVariabel Penelitian
Research variables consist of independent variables (Independent) and dependent variables (Dependent). This model can be developed into SEM Model 1 to SD. SEM model 4 with various variations of the SEM equation model: The dependent (dependent) variable is Gross National Product (GNP) = (Y1) and GDP (Gross Domestic Product) = Y2. Meanwhile, the independent variable is Financial Performance, namely: ROA (Return On Assets) = X1;
ROE (Return On Equity) (X2); ROI (Return On Investment) (X3); CAR (Current Assets to ratio)
= (X4), DER (Debt Equity Ratio)= (X5), DAR (Debt Assets Ratio) =(X6); NPM (Net Profitability Margin)= (X7) & Tobin's Q= (X8). Meanwhile, the GCG (Good Corporate Governance) & GGE (Green Growth Economy) variables are moderating variables which can strengthen or weaken the influence between variables X and Y. The various variables can be developed into SEM 1 to SD models. SEM 4 above. Various models can be used as tools to create the various hypotheses above. Meanwhile, the population and sample are development board companies whose shares are listed on the IDX from 2020 to 2023 and have complete financial report data, there are 372 as the population. Then it was summarized into 80 development board companies that had complete financial reports reported for 3 consecutive years and had 17 annual reports.
B. Data analysis methods.
The main data analysis methods in this research are using the t test or t test, F test or F- test, R Squared or Chie Square test, Multiple Linear Regression Test & MRA Test. To test the normality of research data, the Classical Assumption Test is used. A description of the data can be seen in the Attachments.
3. Results And Discussion
Recapitulation Table of Data Analysis Results for Variables X and Y
No Hasil Analisis Data
Regresi Berganda UJI F (F-TEST)
Uji t (T-TEST)
R 2 MRA
(MODERATING REGRESION ANALIZE)
1 Analisis 1 Fhitung 17,137 >
Ftabel 2,07 dan nilai signifikan 0,000 <
0,05, artinya model yang digunakan telah fit.
1. Variabel ROA (X1) nilai t hitung 2,525 lebih besar dari pada t tabel sebesar 1,994 (2,525 > 1,994) dengan nilai signifikan sebesar 0,014 di bawah 0,05 disimpulkan ROA (X1) berpengaruh signifikan terhadap GNP (Y1).
2. Variabel ROE (X2) nilai t hitung 3,544 lebih besar dari pada t tabel sebesar 1,994 (3,544 > 1,994) dengan nilai signifikan sebesar 0,001 di bawah 0,05 disimpulkan ROE (X2) berpengaruh
Hasil perhitungan diperoleh nilai koefisien determinasi (R2) sebesar 0,688. koefisien determinasi (R2) 68,8%
Artinya Variabel Y dapat dijelaskan oleh variabel X yang terdiri dari
ROA (X1),
ROE (X2), ROI
(X3), CAR
(X4), DER
(X5), DAR
(X6), NPM
(X7), dan
Tobin’s Q (X8) terhadap GNP (Y1) melalui
Pengaruh ROA (X1) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi. Nilai t hitung regresi MRA ROA (X1) sebesar -1,283 lebih kecil dari pada t tabel sebesar -1,994 (-1,283 < -1,994) dengan nilai signifikan sebesar 0,204 di atas 0,05. Disimpulkan secara tidak langsung ROA (X1) melalui GGE (Z1) tidak mampu mempengaruhi GNP (Y1) yang berarti ditolak.
Pengaruh ROE (X2) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA ROE (X2) sebesar -2,281 lebih kecil dari pada t tabel sebesar -1,994 (-2,281 < -1,994) dengan nilai signifikan sebesar 0,026 di bawah 0,05. Disimpulkan secara tidak langsung ROE (X2) melalui GGE (Z1) mampu mempengaruhi GNP (Y1) yang berarti diterima.
Pengaruh ROI (X3) terhadap GNP (Y1)
signifikan terhadap GNP (Y1).
3. Variabel ROI (X3) nilai t hitung -2,200 lebih kecil dari pada t tabel sebesar - 1,994 (-2,200 < - 1,994) dengan nilai signifikan sebesar 0,031 di bawah 0,05 disimpulkan ROI (X3) berpengaruh signifikan terhadap GNP (Y1).
4. Variabel CAR (X4) nilai t hitung - 3,781 lebih kecil dari pada t tabel sebesar -1,994 (- 3,781 < -1,994) dengan nilai signifikan sebesar 0,000 di bawah 0,05 disimpulkan CAR (X4) berpengaruh signifikan terhadap GNP (Y1).
5. Variabel DER (X5) nilai t hitung 3,294 lebih besar dari pada t tabel sebesar 1,994 (3,294 > 1,994) dengan nilai signifikan sebesar 0,002 di bawah 0,05 disimpulkan DER (X5) berpengaruh signifikan terhadap GNP (Y1).
6. Variabel DAR (X6) nilai t hitung 4,532 lebih besar dari pada t tabel sebesar 1,994 (4,532 > 1,994) dengan nilai signifikan sebesar 0,000 di bawah 0,05 disimpulkan DAR (X6) berpengaruh signifikan terhadap GNP (Y1).
7. Variabel NPM (X7) nilai t hitung - 1,067 lebih kecil dari pada t tabel sebesar -1,994 (- 1,067 < -1,994) dengan nilai signifikan 0,290 lebih besar 0,05 disimpulkan NPM
(X7) tidak
berpengaruh terhadap GNP (Y1).
8. Variabel Tobin’s Q (X8) nilai t
GGE (Z2)
sebagai variabel mediasi sedangkan sisanya sebesar 31,2% dapat dijelaskan oleh variabel yang lain diluar dari model ini.
melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA ROI (X3) sebesar 3,166 lebih besar dari pada t tabel sebesar 1,994 (3,166 > 1,994) dengan nilai signifikan sebesar 0,002 di bawah 0,05. Disimpulkan secara tidak langsung ROI (X3) melalui GGE (Z1) mampu mempengaruhi GNP (Y1) yang berarti diterima.
Pengaruh CAR (X4) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA CAR (X4) sebesar 2,141 lebih besar dari pada t tabel sebesar 1,994 (2,141 > 1,994) dengan nilai signifikan sebesar 0,036 di bawah 0,05. Disimpulkan secara tidak langsung CAR (X4) melalui GGE (Z1) mampu mempengaruhi GNP (Y1) yang berarti diterima.
Pengaruh DER (X5) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA DER (X5) sebesar -2,315 lebih kecil dari pada t tabel sebesar -1,994 (-2,315 < -1,994) dengan nilai signifikan sebesar 0,024 di bawah 0,05. Disimpulkan secara tidak langsung DER (X5) melalui GGE (Z1) mampu mempengaruhi GNP (Y1) yang berarti diterima.
Pengaruh DAR (X6) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA DAR (X6) sebesar -1,451 lebih brsar dari pada t tabel sebesar -1,994 (-1,451 > -1,994) dengan nilai signifikan sebesar 0,152 di atas 0,05. Disimpulkan secara tidak langsung DAR (X6) melalui GGE (Z1) tidak mampu mempengaruhi GNP (Y1) yang berarti ditolak.
Pengaruh NPM (X7) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA NPM (X7) sebesar -1,326 lebih kecil dari pada t tabel sebesar -1,994 (-1,326 < -1,994) dengan nilai signifikan sebesar 0,190 di atas 0,05. Disimpulkan secara tidak langsung NPM (X7) tidak mampu mempengaruhi GNP (Y1) yang berarti ditolak.
Pengaruh Tobin’s Q (X8) terhadap GNP (Y1) melalui GGE (Z1) sebagai variabel mediasi
Nilai t hitung regresi MRA Tobin’s Q (X8) sebesar 2,271 lebih besar dari pada t tabel sebesar 1,994 (2,271 > 1,994) dengan nilai signifikan sebesar 0,027 di bawah 0,05. Disimpulkan secara tidak langsung Tobin’s Q (X8) melalui GGE (Z1) mampu mempengaruhi GNP (Y1)
hitung -2,503 lebih kecil dari pada t tabel sebesar -1,994 (-2,503 < -1,994) dengan nilai signifikan sebesar 0,015 di bawah 0,05 disimpulkan Tobin’s Q (X8) berpengaruh signifikan terhadap GNP (Y1).
9. Variabel GGE (Z2) nilai t hitung 8,599 lebih besar dari pada t tabel sebesar 1,994 (8,599 > 1,994) dengan nilai signifikan sebesar 0,000 di bawah 0,05 disimpulkan GGE (Z2) berpengaruh signifikan terhadap GNP (Y1).
yang berarti diterima.
4. Closing
1. Conclusion
a. VAR T-test Results – ROA, ROE, ROI, CAR, DER & DAR With VAR- Moderation GGE Moderates Financial Performance on VAR-GNP (Y1) Shown by the t-count value > t-table, and the significance value is below 0.05 This means that it has a significant positive effect, as well as VAR-TOBINS'Q, it is shown that the calculated value is < t-table & the significance value is below 0.05, so it has a significant positive effect on GNP (Y1). Meanwhile, VAR-NPM has no effect on GNP (Y1). The significance value is 0.290 > 0.05. The GGE (Z2) variable has a calculated t value of 8.599 which is greater than the t table of 1.994 (8.599 > 1.994) with a significant value of 0.000 below 0.05, it can be concluded that GGE (Z2) has a significant effect on GNP (Y1). Based on the calculation results, the coefficient of determination (R2) value was 0.688.
coefficient of determination (R2) 68.8% This means that variable Y can be explained by variable NPM (X7), and Tobin's Q (X8) on GNP (Y1) through GGE (Z2) as mediating variables while the remaining 31.2% can be explained by other variables outside this model.
b. Based on the MRA test results, ROE, ROI, CAR, DER & Tobins-q with GGE as a moderating variable are able to moderate VAR - the influence of financial performance on GNP (Y1). Meanwhile, ROA, DER & NPM indirectly through GGE (Z1) as VAR-Moderation Not able to influence VAR-Financial Performance on GNP (Y1) Shows a significance value above 0.05. It is important for the development board companies that are the samples of this research to improve their Liquidity and Profitability performance so that they have an impact
on GGE (Green Growuth Economy) as VAR-Moderation so that they can influence GNP (Y1).
c. Based on the VAR-ROA T-Test Results, ROE, ROI, CAR, DER, DAR, NPM &
Tobinsq have an influence on GNP (Y1) as shown by a significance value of
<0.05. Meanwhile, VAR-GCG (Z2) as VAR-Moderation is able to moderate the influence of financial performance on GNP (Y1).
d. Based on the MRA Test Results, the Effect of ROA, ROI, CAR, & Tobinsq on GNP (Y1) through GCG (Z1) as VAR- Moderation. Able to moderate the Effect of Financial Performance on GNP (Y1). This means that indirectly through GCG (Z1) it is able to influence GNP ( Y1) which means according to the hypothesis.
Meanwhile, ROE, DER, DAR & NPM are concluded through GCG (Z1) as VAR-Mediation is not able to influence GNP (Y1). VAR-ROA, ROI, ROE, CAR, DER & NPM with an average value above 0.05 is concluded to have no significant effect on GDP (Y2). Meanwhile, Tobinsq & GGE (Z2) is concluded to have an effect on GDP (Y2).
e. Based on the MRA-ROA Test Results, ROI, CAR & Tobinsq Through GCG (Z1) as a moderating variable has a significant positive effect of 0.001 < 0.05 on GNP (Y1). Meanwhile, ROE, DER, DAR & NPM through GCG (Z1) are unable to influence GNP (Y1) as indicated by an average significance value of 0.789;
0.288; 0.938; 0.871 above 0.05 So it is rejected. This means that GCG (Z1) as a moderating variable is unable to influence Financial Performance on GNP (Y1).
f. Tobin's Q (X8) variable t value -2.745 is smaller than the t table of -1.994 (- 2.745 < -1.994) with a significant value of 0.008 below 0.05, it can be concluded that Tobin's Q (X8) has a significant effect on GDP (Y2) . The GGE (Z2) variable has a calculated t value of 4.098 which is greater than the t table of 1.994 (4.098 >
1.994) with a significant value of 0.000 below 0.05, it can be concluded that GGE (Z1) has a significant effect on GDP (Y2). While the variables ROA (X1), ROE (X2), ROI (X3), CAR (X4), DER (X5), DAR (X6), and NPM (X7), with an average significant value above 0.005, it is concluded that no significant effect on GDP (Y2). Based on the MRA-ROA Test Results, ROE, Through GGE (Z1) as VAR- Moderation Indirectly Not able to moderate the Effect of Financial Performance on GDP (Y2) Shown by a significance value of 0.316; 0.773 is above 0.05, so it is rejected. Meanwhile, Tobinsq, ROI, CAR, DER, DAR &
NPM through GGE (Z2) are able to moderate financial performance towards GDP (Y2). Shown as a significance value of <0.05, so it is accepted.
g. VAR- ROA, ROE, ROI CAR, DER, DAR, NPM & Tobinsq and GGE are concluded to have a significant influence on GDP (Y2). The average significance value is shown to be below 0.05, which means the hypothesis is accepted.
Meanwhile, based on the MRA test results, it can be concluded indirectly that ROA, ROI through GGE (Z2) is able to influence GDP (Y2), which means it is acceptable. The calculated t value of the MRA ROA (X1) regression is 3.416 which is greater than the t table of 1.994 (3.416 > 1.994) with a significant value of 0.001 & 0.026 below 0.05. VAR- ROE on GDP (Y2) through GGE (Z2) as a mediating variable is unable to influence GDP (Y2) which means it is rejected.
Shown is a significance value of 0.069.>0.05, as well as VAR-CAR. The
influence of CAR (X4) on GDP (Y2) through GGE (Z2) as a mediating variable.
The calculated t value of the MRA CAR regression (X4) is 0.354 which is smaller than the t table of 1.994 (0.354 < 1.994) with a significant value of 0.725 above 0.05. It can be concluded indirectly that CAR (X4) through GGE (Z2) is unable to influence GDP (Y2), which means it is rejected. Meanwhile, DER to GDP (Y2) via GGE (Z2) as a mediating variable. The calculated t value of the MRA-DER regression is -2.632 which is smaller than the t table of -1.994 (-2.632
< -1.994) with a significant value of 0.011 below 0.05. It can be concluded that DER indirectly through GGE (Z2) is able to influence GDP (Y2), which means it is acceptable. The effect of DAR on GDP (Y2) through GGE (Z2) as a mediating variable. The calculated t value of the MRA DAR regression (X6) is -1.281 which is smaller than the t table of -1.994 (-1.281 < -1.994) with a significant value of 0.205 above 0.05. It is concluded indirectly that DAR (X6) through GGE (Z2) is unable to influence GDP (Y2), which means it is rejected. The influence of NPM (X7) on GDP (Y2) through GGE (Z2) as a mediating variable. The calculated t value of the MRA NPM (X7) regression of 0.193 is smaller than the t table of 1.994 (0.193 < 1.994) with a significant value of 0.848 above. 0.05. It can be concluded that indirectly NPM (X7) through GGE (Z2) is able to influence GDP (Y2), which means it is rejected. The influence of Tobin's Q (X8) on GDP (Y2) through GGE (Z2) as a mediating variable. The calculated t value of Tobin's Q (X8) MRA regression of 3.870 is greater than the t table of 1.994 (3.870 >
1.994) with a significant value of 0.000 in below 0.05. It can be concluded that indirectly Tobin's Q (X8) through GGE (Z2) is able to influence GDP (Y2), which means it is accepted.
h. Based on the MRA Mediation Test Results, the following results were obtained:
The effect of ROA, (X1) on GDP (Y2) through GCG (Z2) as a mediating variable. The calculated t value of the MRA ROA (X1) regression is 0.472 which is smaller than the t table of 1.994 (0.472 < 1.994) with a significant value of 0.639 above 0.05. It is concluded indirectly that ROA (X1) through GCG (Z2) is unable to influence GDP (Y2), which means it is rejected. Meanwhile, ROE, ROI, CAR, DER, & NPM and Tobinsq on GDP (Y2) through GCG (Z2) as variables. It is concluded Indirectly, ROE through GCG (Z2) is able to influence GDP (Y2), which means it is acceptable. Shown is a significance value of <0.05.
The influence of DAR (X6) on GDP (Y2) through GCG (Z2) as a mediating variable. The calculated t value of the MRA DAR regression (X6) is 0.324, which is smaller than the t table of 1.994 (0.324 < 1.994) with a significant value of 0.747 above 0.05. It was concluded indirectly that DAR (X6) through GCG (Z2) was unable to influence GDP (Y2), which means it was rejected. Analysis Results-6. Based on the MRA Mediation Test Results, the following results were obtained: The effect of ROA (X1) on GDP (Y2) through GCG (Z2) as a mediating variable. The calculated t value of the MRA ROA (X1) regression is 0.472 which is smaller than the t table of 1.994 (0.472 < 1.994) with a significant value of 0.639 above 0.05. It can be concluded indirectly that ROA (X1) through GCG (Z2) is unable to influence GDP (Y2), which means it is rejected. Likewise DAR. Meanwhile, VAR-ROE, ROI, CAR, DER, NPM & Tobins on GDP (Y2)
through GCG (Z2) as mediating variables with a significant value of 0.024 below 0.05. It can be concluded that indirectly VAR- ROE, ROI, CAR, DER, NPM &
Tobinsq through GCG (Z2) is able to influence GDP (Y2) which means it is acceptable.
2. Suggestions
a. Based on the conclusions explained in chapter iv, the following are recommended: (1) Based on the results of Analysis 1, it shows that ROA, DAR &
NPM, concluded indirectly through GGE (Z1), are unable to influence GNP (Y1), which means the hypothesis is rejected. This means that the return on operational assets is low, so it is important to increase ROA, which means Return On Assets, because it is estimated that the Return on Operational Assets of Development Board Companies will have a positive impact on increasing Turnover which can ultimately increase Operational Profit so that it can encourage ROA moderated by GGE to have a positive effect. significant to GNP (Y1).
b. Likewise, NPM, if a company's net profit margin increases periodically every year, it will encourage NPM contribution through GGE as a moderating variable on GNP (Y1) so that NPM has a significant positive effect on GNP (Y1). (2) Meanwhile ROE, DER, DAR & NPM are concluded through GCG (Z1) as VAR- Mediation is not able to influence GNP (Y1). VAR-ROA, ROI, ROE, CAR, DER
& NPM with an average value above 0.05 is concluded to have no significant effect on GDP (Y2). It is recommended that ROE, DER, & NPM be increased so that they are able to encourage GCG (Z1) as VAR-Moderation to moderate Financial Performance against GNP (Y1),
c. Meanwhile, DAR is actually reduced in terms of the use of debt for operations, because the higher the use of debt for operations, the smaller the profit that can be obtained because most of it is to pay the debt burden. If it is not balanced to increase other VARs which encourage net profit to increase then VAR- ROE, DER, DAR & NPM will be unable to increase GNP (Y1).
d. Likewise, the test results for MRA-ROA, ROE, via GGE (Z1) as VAR- Moderation Indirectly unable to moderate the influence of financial performance on GDP (Y2) are shown by a significance value of 0.316; 0.773 is above 0.05, so it is rejected. So to increase ROA, ROE is able to encourage GGE (Z1) to moderate Financial Performance towards GDP (Y2) so that GDP increases. (4) VAR-ROE on GDP (Y2) through GGE (Z2) as a mediating variable is unable to influence GDP (Y2), which means it is rejected. Shown is a significance value of 0.069.>0.05,
e. Likewise VAR-CAR. Influence of CAR (X4) It can be concluded indirectly that CAR (X4) through GGE (Z2) is unable to influence GDP (Y2), which means it is rejected. So it is important to increase the CAR & ROE value so that it can moderate financial performance towards GDP (Y2). Based on the MRA Mediation Test Results, the following results were obtained: The effect of ROA, (X1) on GDP (Y2) through GCG (Z2) as a mediating variable. The calculated t value of the MRA ROA (X1) regression is 0.472 which is smaller than the t table of 1.994 (0.472 < 1.994) with a significant value of 0.639 above 0.05. It can be
concluded indirectly that ROA (X1) through GCG (Z2) is unable to influence GDP (Y2), which means it is rejected. Likewise, it is concluded that indirectly DAR (X6) through GCG (Z2) is unable to influence GDP (Y2), which means it is rejected. So it is recommended that it is important to increase ROA but reduce DAR.
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